(1) Field of the Invention
The present invention relates to a sorting and inspection apparatus, and particularly an optical sorting and inspection apparatus, for example for inspecting and then sorting bulk food stuffs such as grain, rice, nuts, pulses, fruit and vegetables. Examples of such apparatus are described in International Patent Publication No: WO98/018574, European Patent Publication No: EP0838274, US patent Specification No: U.S. Pat. No. 4,630,736 and GB Patent Publication No. GB2471885, the entire disclosures of which are hereby incorporated by reference.
(2) Description of Related Art
In machines of these types, a stream of products to be sorted is delivered, usually in free flight, through an imaging zone and a sorting zone. In the imaging zone, designated defects are looked for, and in the sorting zone, any products on which defects have been identified, and which products are thus to be rejected, are removed or separated from the stream of products. The removal is usually by way of one or more blasts of gas, such as air, from one or more ejectors disposed adjacent the stream of products.
In such machines, the required throughput is normally determined by the production rates elsewhere in the processing plant. Normally though, the required throughput is high and is typically measured in tonnes per hour, whereby for small products, the throughput is very rapid, with large numbers being sorted every second.
Food producers often use sorting and inspection apparatus, such as optical sorting machines, to sense defects in their foodstuffs, and thus to allow the removal of any defective, i.e. non-standard, products from the product stream. This in turn allows the sorted product to meet a client's agreed grade or quality standard, but yet while still maximising the total production yield from the unsorted product stream to the best extent possible, in a given timeframe. The quality standard usually specifies individual maximum levels of contamination for different types of defect. For example, when sorting rice, the defects might be insect-damaged “peck-grains”, or chalky grains or yellow grains, with maximum levels for these contaminants being say less than 0.1% peck, less than 1% chalky and less than 0.2% yellow. Some customers also specify restrictions on the numbers of grey grains.
As used herein, the term “defect” or “defective” should be understood to include both blemishes on articles being sorted and whole articles/products which are unsatisfactory for that reason, or for another reason. It can also include foreign material or extraneous product.
Optical sorting machines identify defects in the product being sorted by using known techniques, such as by continuously analysing images of product (or parts of products) in the stream, taken at the imaging zone using sensors. Output signals from an image analyser can then be used to allow a control system to instruct the ejectors as appropriate, so as to eject the defects identified in the images, and thus also the products featuring those defects.
Usually the sensors are optimised to detect a particular type of defect. However, a sensor, or a line on a sensor, can be optimised for a specific sorting criteria, which sensor or line on a sensor may then also happen to usefully detect another type of defect, either because a product has more than one type of defect or because the sorting criteria are not wholly independent of each other. Optimisation may be by having each sensor or line of sensor look at a particular wavelength of light, or set of wavelengths of light, such as by providing the sensor or the line of pixels of the sensor with a specific filter. Alternatively or additionally, the light source may be tuned to provide at the viewing window of the sensor, or for a line thereof, an illumination of the product steam characterised by a desired wavelength or set of wavelengths of light, or with an illumination that omits certain undesired wavelengths, so as to suit the defect detection optimisation. This also can be achieved with filters, for filtering the emitted light prior to illuminating the product stream. Flashing lights can also allow alternating light colours.
With regard to that optimisation, there is no certainty that a given optimisation will offer exclusive detection for a specific form of defect. For example, an optimised detection criteria for rice, designed to detect peck-grains, may also identify some chalky and some yellow grains for removal. Furthermore, even though a particularly optimised detection criteria will typically identify the majority of one type of defect, it can also incorrectly classify some good products as being defective, since the optimisation is not necessarily optimised or appropriate as a means of detection for other forms of defect. For this reason, different criteria detections, using more than one optimisation, can be carried out either simultaneously using prisms, or in series as the product passes down or across through the imaging zone, again potentially using a flashing light source with sequential variable colours, or using different filters on two or more sensors or two or more lines of a sensor). For example, a first defect criteria detection may be carried out in a first part or line of the imaging zone, potentially using a first flash of illumination, perhaps of a first colour, e.g. blue, and a second defect criteria detection may be carried out in a fractionally spaced, usually lower, second part or line of the imaging zone, potentially using a second flash of illumination, perhaps of a different colour, e.g. red. These serial detections then allow both for two optimised detections to be carried out so as to allow the sensor(s) to optimally check for two or more different defects, and thus offer detection by means of individual optimisations. Where appropriate or possible given the optimisations used and the given characteristics of the detected product, it could also allow for cross-checking or correlation between the sequential or separate detections made by the detection circuit.
A problem occurs, however, with sequential detections, whether using flashing illuminations or frame by frame detections, in terms of matching up one detection with the next, so as to allow a cross-check or correlation to be performed, and that is related to the fact that whereas the frequency of the flashing, or the frequency of the image frame rate, or both, is typically fixed for a given viewing zone of a sorting apparatus, the speed of passage (velocity) of the individual, sequential, products in the product stream passing through that viewing zone is not fixed at the imaging zone—some products are travelling faster than others. After all, a product's velocity can depend on a number of situational characteristics, such as the design/features of the apparatus, the characteristics of the products themselves, the ambient environmental conditions, and the individual interactions between the various elements and products involved. For example, in rice sorting equipment, where the rice grain is passing through the viewing zone effectively in free fall, the velocities in the feed plane, i.e. through the imaging zone, are typically going to be anywhere between 3.5 m/s and 4.3 m/s. As a result, the specific timing of the commencement of the passage of a particular product into each part of the viewing zone is somewhat random. As such, there can be variations in the detection images used for the two or more sequential steps in the detection process, from one line or one sensor to the next, thereby making it hard to cross-check the separate detections, and this can lead to variable detection accuracy. Attempts in the past to compensate for this have included trying to synchronise timing of flashed illumination to the products in the product stream, but that is too complicated, especially since a sorting apparatus may feature many separate product streams, each steam potentially being perhaps no more than a meter wide with a product flow in the order of more than one tonne per hour, and thus very densely populated with grains, and it is possible that the average speeds of those separate product streams will themselves be different or non-constant over time, since ambient condition can change or since different streams on a machine may have different functions, i.e. a flat or primary stream may have an average speed of 3.9 m/s and a re-sort or channelled stream may have an average speed of perhaps 3.5 m/s, and yet both may be on the same machine. Further, the multiple product streams are likely each to have their own viewing zone, and thus may have their own sensor(s) and light source(s). Therefore the product streams may be desired to be configured/synchronised separately for optimising detection performance.
As such, optimally setting up the system so as to allow a correlation of detections from one sensor or line to the next, i.e. for comparing detections on supposedly the same portion of a product in a given product stream, and doing the same for every product in every product stream, is less than straightforward.